The rapid digital transformation of the oil and gas sector is driving the evolution of Supervisory Control and Data Acquisition (SCADA) systems beyond traditional capabilities. As field operations become increasingly complex, geographically distributed, and data-intensive, legacy SCADA architectures are often insufficient to support the demands of real-time monitoring, control, and predictive maintenance. This paper explores the emergence of next-generation SCADA architectures designed to enhance field automation, ensure operational reliability, and enable intelligent remote control across upstream oil and gas environments. The study begins by examining the limitations of conventional SCADA systems, including centralized control, limited scalability, poor interoperability, and delayed response times. It then presents a comprehensive analysis of modern SCADA advancements such as edge computing, cloud-native platforms, IIoT (Industrial Internet of Things) integration, and cybersecurity-enhanced protocols. These components are positioned as key enablers of decentralized intelligence, high-frequency data processing, and autonomous control loops across drilling sites, pipelines, and production assets. Further, the paper investigates use cases of advanced SCADA deployment in various oil and gas fields, highlighting their impact on downtime reduction, production optimization, and environmental compliance. Emphasis is placed on the strategic role of digital twins, AI-driven analytics, and multi-layered control hierarchies in creating agile and resilient automation frameworks. The findings underscore that transitioning to next-generation SCADA is not merely a technological upgrade but a transformational shift requiring cross-disciplinary collaboration, infrastructure modernization, and robust governance. The paper concludes with a roadmap for industry stakeholders to adopt scalable, secure, and interoperable SCADA ecosystems aligned with future energy and digitalization goals.